Evaluation of land surface phenology from VIIRS data using time series of PhenoCam imagery
Evaluation of land surface phenology from VIIRS data using time series of PhenoCam imagery
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DOI：
10.1016/j.agrformet.2018.03.003
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发表时间：
2018-06
影响因子：
6.2
通讯作者：
Xiaoyang Zhang;Senthilnath Jayavelu;Lingling Liu;M. Friedl;G. Henebry;Yan Liu;C. Schaaf;A. Richardson;Joshua Gray
中科院分区：
文献类型：
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作者：
Xiaoyang Zhang;Senthilnath Jayavelu;Lingling Liu;M. Friedl;G. Henebry;Yan Liu;C. Schaaf;A. Richardson;Joshua Gray
为了监测气候变化和生态系统动态，已经从各种卫星仪器的时间序列中广泛地提取了陆地表面物候(LSP)。然而，对LSP数据集的质量的任何评估都是相当具有挑战性的，因为对有限数量的单个乔木、灌木或其他植物的现场观测很少能代表在单个卫星像素上采样的景观。此外，反映植被季节性生物物理特征的植被指数不同于人类在地面观察到的特定植物生活史阶段，但与之相关。这项研究是首次使用MODIS LSP产品和美国毗邻地区PhenoCam网络2013至2014年的观测数据对LSP产品进行全面评估，该产品来自可见光红外成像辐射计套件(VIIRS)。PhenoCam以非常高的频率观测景观上的植被树冠，提供几乎连续的树冠状态，并能够使用在概念上与卫星数据相似的植被指数来估计离散物候。从逐日VIIRS NDVI(归一化差异植被指数)和EVI2(两波段增强植被指数)时间序列分别反演了6个物候期(返青开始、返青中期、成熟开始、衰老开始、中期衰老和休眠开始)。同样，也分别使用GCC(绿色色度坐标)和植被对比度指数(VCI)从PhenoCam数据的30min时间序列中提取了6个物候日期。由VIIRS NDVI和EVI2和PhenoCam GCC和VCI得到的物候数据与植被返青期基本相似，但在衰老期有较大差异。尽管所有指数都有效地捕捉到了绿叶的发育，但由于它们能够跟踪衰老叶片的混合颜色，因此出现了表现上的差异。物候CAM、GCC和VCI物候观测与VIIRS EVI2的物候数据比VIIRS NDVI的物候数据更符合。此外，VIIRSEVI2物候指标与PhenoCam VCI的物候指标更接近，而不是PhenoCam GCC的时间序列。总体而言，VIIRS EVI2和PhenoCam VCI物候数据之间的平均绝对差异在返青期为7-11天，在衰老期为10-13天。森林的差异较小，其次是草原和农田，然后是稀树草原。最后，将VIIRS EVI2的物候数据与MODIS的物候数据进行了比较，除开始衰老外，两者的平均绝对差异小于1周，两者吻合较好。这些结果首次证明了VIIRS LSP探测的不确定度上限以及与MODIS LSP产品的连续性。
Land surface phenology (LSP) has been widely retrieved from time series of various satellite instruments in order to monitor climate change and ecosystem dynamics. However, any evaluation of the quality of LSP data sets is quite challenging because the in situ observations on a limited number of individual trees, shrubs, or other plants are rarely representative of the landscape sampled in a single satellite pixel. Moreover, vegetation indices detecting biophysical features of vegetation seasonality are different from (but related to) the specific plant life history stages observed by humans at ground level. This study is the first comprehensive evaluation of the LSP product derived from Visible Infrared Imaging Radiometer Suite (VIIRS) data using both MODIS LSP products and observations from the PhenoCam network across the Contiguous United States during 2013 and 2014. PhenoCam observes vegetation canopy over a landscape at very high frequency, providing nearly continuous canopy status and enabling the estimate of discrete phenophase using vegetation indices that are conceptually similar to satellite data. Six phenological dates (greenup onset, mid-greenup phase, maturity onset, senescence onset, mid-senescence phase, and dormancy onset) were retrieved separately from daily VIIRS NDVI (normalized difference vegetative index) and EVI2 (two-band enhanced vegetation index) time series. Similarly, the six phenological dates were also extracted from the 30-min time series of PhenoCam data using GCC (green chromatic coordinate) and VCI (vegetation contrast index) separately. Phenological dates derived from VIIRS NDVI and EVI2 and PhenoCam GCC and VCI were generally comparable for the vegetation greenup phase, but differed considerably for the senescence phase. Although all indices captured green leaf development effectively, performance discrepancies arose due to their ability to track the mixture of senescing leaf colors. PhenoCam GCC and VCI phenological observations were in better agreement with the phenological dates from VIIRS EVI2 than from VIIRS NDVI. Further, the VIIRS EVI2 phenological metrics were more similar to those from PhenoCam VCI than from PhenoCam GCC time series. Overall, the average absolute difference between the VIIRS EVI2 and PhenoCam VCI phenological dates was 7–11 days in the greenup phase and 10–13 days in the senescence phase. The difference was smaller in forests, followed by grasslands and croplands, and then savannas. Finally, the phenological dates derived from VIIRS EVI2 were compared with MODIS detections, which showed a good agreement with an average absolute difference less than a week except for the senescence onset. These results for the first time demonstrate the upper boundary of uncertainty in VIIRS LSP detections and the continuity to MODIS LSP product.